Proceedings of the 2023 8th International Conference on Engineering Management (ICEM 2023)

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Research on the method of machine tool running state management based on digital twin

Authors
Yu Hang1, *, Fang Xifeng1, 2, Feng Linhao1
1School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212100, China
2Jiangsu Key Laboratory of Advanced Manufacturing Technology, Huaian, 223003, China
*Corresponding author. Email: 1802613134@qq.com
Corresponding Author
Yu Hang
Available Online 11 December 2023.
DOI
10.2991/978-94-6463-308-5_25How to use a DOI?
Keywords
digital twin; Rough set; OC-SVM; Running status management
Abstract

In order to solve the problems of low monitoring accuracy and inability to handle abnormalities in industrial production, a digital twin based machine tool operation status management method is proposed. On the basis of building the twin model architecture of machine tool operation state management and establishing the method flow, the data flow between virtual machine tools and physical machine tools is realized by building virtual machine tools and establishing communication with physical machine tools. By combining attribute reduction based on rough sets and one-class support vector machine (OC-SVM) algorithms, accurate recognition and warning of machine tool abnormal states were achieved. The abnormal states were relieved by optimizing cutting parameters using BP neural network and virtual real data fusion method. Finally, the effectiveness and practicality of this method were verified through an example of machining a certain type of marine diesel engine frame.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 8th International Conference on Engineering Management (ICEM 2023)
Series
Atlantis Highlights in Engineering
Publication Date
11 December 2023
ISBN
978-94-6463-308-5
ISSN
2589-4943
DOI
10.2991/978-94-6463-308-5_25How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yu Hang
AU  - Fang Xifeng
AU  - Feng Linhao
PY  - 2023
DA  - 2023/12/11
TI  - Research on the method of machine tool running state management based on digital twin
BT  - Proceedings of the 2023 8th International Conference on Engineering Management (ICEM 2023)
PB  - Atlantis Press
SP  - 231
EP  - 243
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-308-5_25
DO  - 10.2991/978-94-6463-308-5_25
ID  - Hang2023
ER  -